压缩感知在有限反馈预编码中的应用研究

发布时间：2018-06-30 04:41

本文选题：多输入多输出 + 压缩感知　；参考：《河南工业大学》2017年硕士论文

【摘要】：多输入多输出(MIMO)技术通过在基站端和用户端配备多根天线,可以突破有限带宽及发射功率的限制,实现对系统的吞吐量提高,进而达到有效改善系统频谱利用率的效果。正交频分复用(OFDM)是一种多载波调制复用技术,其技术特点是每个子载波都是相互正交的,且循环前缀作为保护间隔,避免了不同子载波因重叠而产生的干扰。OFDM对于频率选择性衰落改善、系统频谱利用率的提高都有极好的效果。因此MIMO与OFDM技术两者相结合,不仅能够成倍的提高系统吞吐量,同时降低误码率。为进一步提高系统的整体性能,可在发送端对发送的数据流进行预编码处理。预编码技术前提条件是:发送端已获取完备的信道状态信息,而反馈完整的信道状态信息将占用反馈链路大量的频带资源,因此,如何利用少量的反馈数据而获取与完整信道状态信息近乎相同的效果是近几年的研究热点。本文将压缩感知技术应用到有限反馈预编码系统中,并针对如何减少反馈数据量和提高重构精度方面进行了研究,主要完成了以下工作:1.为减少链路反馈开销,提出了基于压缩感知的有限反馈预编码算法,并利用Karhunen-Loève变换(KL变换)对估计所得的完整信道信息进行稀疏表示,仿真结果表明,在不损失信道特征信息的前提下,进一步减少了反馈数据量。2.针对传统OMP算法缺陷,提出了基于两次筛选和重构加权最小二乘法的改进OMP算法,并与传统OMP、ROMP算法进行仿真对比分析,验证了改进算法的有效性。3.把压缩感知应用扩展到大规模MIMO系统有限反馈中,并对提出的联合稀疏改进算法进行仿真分析,结果表明:联合稀疏可选择更加合适的观测矩阵,有利于减少反馈链路的开销。
[Abstract]:Multi input and multiple output (MIMO) technology is equipped with multiple antennas at the base station and the user side, which can break through the limited bandwidth and transmit power, so as to improve the throughput of the system and improve the efficiency of the system spectrum efficiency. Orthogonal frequency division multiplexing (OFDM) is a multi carrier modulation multiplexing technology. The subcarriers are mutually orthogonal, and the cyclic prefix is used as the protection interval to avoid the interference.OFDM caused by the overlapping of different subcarriers to improve the frequency selective fading and the enhancement of the frequency spectrum utilization of the system. Therefore, the combination of MIMO and OFDM technology can not only improve the system throughput, but also multiply the system throughput. To further improve the bit error rate. In order to further improve the overall performance of the system, the transmitted data stream can be precoded at the transmitter. Precoding is that the transmitter has acquired complete channel state information, and the feedback complete channel state information will take up a large number of band resources in the feedback link, thus how to use a small amount of information. Feedback data to obtain nearly the same effect as the complete channel state information is the hot spot in recent years. This paper applies compressed sensing technology to the finite feedback precoding system, and studies how to reduce the amount of feedback data and improve the accuracy of reconfiguration. The following work is completed: 1. to reduce link feedback The finite feedback precoding algorithm based on compressed sensing is proposed, and the Karhunen-Lo y ve transform (KL transform) is used to sparse representation of the estimated complete channel information. The simulation results show that, without losing the channel feature information, the feedback data amount.2. is further reduced to the defect of the traditional OMP algorithm. The two time screening and reconstructing the improved OMP algorithm with weighted least squares, and comparing with the traditional OMP and ROMP algorithm, the validity of the improved algorithm is verified..3. is extended to the finite feedback of large-scale MIMO system, and the proposed joint sparse improvement algorithm is simulated and analyzed. The results show that the joint sparse can be sparse. Choosing a more suitable observation matrix is helpful to reduce the cost of feedback link.
【学位授予单位】：河南工业大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3

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